🎯MCP vs Direct API Calls

MCP is designed to abstract the complexity of traditional APIs (which were built for developers not for AI models).
While in direct API Calls we have to hardcode every possible interaction. e.g we have to explicitly define every endpoint and parameter in advance. And a lot of integration burden for every individual API (e.g REST, GraphQL).

🤔What is MCP used for ?

We use MCP while building AI agents and applications that require dynamic, autonomous and context aware interactions with external tools and data. Like while you ask LLM "what is the weather in California?", as it does not have real time data, so it make an external tool call to a weather API to fetch the data and then it serve to us.

🧩MCP can solve following problems-

1. Dynamic Tool Discovery: It allows AI agents to dynamically discover and understand available tools and their capabilities at runtime.

2. Standardization: It provides a single, unified protocol for AI-tool communication, it act as a universal connector like USB-C. Meaning once an AI agent understands MCP, it can potentially use any MCP-compliant service, which reduces integration burden on developer.

3. Context and State Management: It supports stateful sessions and bidirectional context streaming, allowing AI agents to maintain conversation history and build upon previous interactions. Meanwhile traditional APIs are stateless, requiring developers to manually manage and pass all necessary context with each independent request.

4. Enhanced Security: Direct API access for AI models can be risky, exposing sensitive API keys and potentially allowing models to make unintended or malicious requests. MCP acts as a controlled layer that abstracts raw credentials or network details from AI.

5. Simplified Workflow: MCP enables the creation of powerful, high-level tools that abstract complex, multi-step operations into a single AI command.

📝Important: We often user a hybrid approach for real world use cases. Although MCP is optimized for AI specific tasks, but it lacks maximum control, predictable/stable workflow (e.g payment processing or user authentication), latency due multistep workflow which include reasoning and context.